code: def edge_softmax(gidx, logits, eids=ALL, norm_by="dst"):
      @tf.custom_gradient
      def _lambda(logits):
          return edge_softmax_real(gidx, logits, eids, norm_by)
  
      return _lambda(logits)
  
imports: import numpy
  import tensorflow
  from ..._sparse_ops import _bwd_segment_cmp, _csrmask, _csrmm, _csrsum, _gsddmm, _gspmm, _scatter_add, _segment_reduce
  from ...base import ALL, is_all
  from ...heterograph_index import create_unitgraph_from_csr
  from .tensor import asnumpy, context, copy_to, tensor, zerocopy_from_numpy
label_desc: Use image node_id 13 for calling a global function with example usage: edge_softmax(gidx, logits, eids, norm_by) and returns: _lambda, edge_softmax_real